This course provides an analytical framework to help you evaluate key problems in a structured fashion and will equip you with tools to better manage the uncertainties that pervade and complicate business processes. To this end, the course aims to cover statistical ideas that apply to managers by discussing two basic themes: first, is recognizing and describing variations present in everything around us, and then modeling and making decisions in the presence of these variations. The fundamental concepts studied in this course will reappear in many other classes and business settings. Our focus will be on interpreting the meaning of the results in a business and managerial setting.
While you will be introduced to some of the science of what is being taught, the focus will be on applying the methodologies. This will be accomplished through use of Excel and using data sets from many different disciplines, allowing you to see the use of statistics in very diverse settings. The course will focus not only on explaining these concepts but also understanding the meaning of the results obtained.
You will be able to:
• Test for beliefs about a population
• Compare differences between populations
• Use linear regression model for prediction
• Use Excel for statistical analysis
This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/.
In the course orientation, you will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course.
Module 1: Hypothesis Testing
Watch any infomercial and you hear many outrageous promises. Use this cream and your skin will look 80% firmer! Use this supplement and you will lose 10 pounds in the first 10 days! Are they telling you the truth? Are they all lying? The only way to know the answer to any of these questions is to scientifically test the claim being made – that is what we call hypothesis testing and what we will learn in this module.
Module 2: Statistical Inference Based on Two Samples
Does the medicine a person is taking to treat his condition really work better than a sugar pill? Is the new chip-enabled credit card more secure than the magnetic card? How do you know whether the claims being made about anything being “better than” or “faster than” a competitor are true? In this module we will learn to make this comparison.
Module 3: Simple Linear Regression
Does your job involve a lot of sitting? If so, you are at higher risk of coronary heart disease. How do I know this? We got to know the relationship between coronary heart disease and sitting when researchers studied a cohort of London bus drivers and bus conductors from 1947 to 1972. If you want to know more, then read on!
Module 4: Multiple Linear Regression
You are trying to predict next month’s sales numbers. You know that dozens, maybe even hundreds, of things like the weather, competitor’s promotions, rumors, etc. can impact the number. You talk to five people and each one has an idea about what makes the biggest impact, and the only thing they offer is “trust me.” Do you wish there was a better way of doing this rather than relying on blind faith? Well, there is. We can use Multiple Regression to sort through this mess and bring the focus to factors that really do matter.